Background: Colonization of soft denture liners by Candida albicans and other microorganisms continued to be a serious problem. The aim of this study was to evaluate the effect of incorporating silver nanoparticles into heat cured acrylic-based soft denture liner on the antifungal activity, and on water sorption, solubility, shear bond strength and color change of the soft lining material. Furthermore, evaluating the amount of silver released. Materials and methods: Silver nanoparticles were incorporated into soft denture liner in different percentages (0.05%, 0.1% and 0.2% by weight). Four hundred and twenty specimens were prepared and divided into five groups according to the test to be performed. The antifungal activity of the soft liner/AgNPs composite was evaluated in three different periods by using (viable count of C. albicans and disk-diffusion test). The amount of silver released in artificial saliva was measured by atomic absorption spectroscopy. The water sorptions, solubility, shear bond strength and color change was measured and the results were statistically analyzed. Results:All experimental groups showed a highly significant decrease in colony forming units of C. albicans in comparison to control group. There was no inhibition zone around any test specimen of any test group. There was no silver detected to be released. The addition of AgNPs resulted in a highly significant decrease in water sorption, while only 0.2% group showed highly significant decrease in solubility. Non significant differences in shear bond strength were found. A highly significant increase in light absorption percentage was observed in all experimental groups. Conclusion: The addition of AgNPs helps to produce soft denture liner with antifungal properties. Silver was not detected to be released. This addition resulted in decrease in water sorption, and did not affect the shear bond strength and it increased the opacity of the material.
The specifications of lubricating oil are fundamentally the final product of materials that have been added for producing the desired properties. In this research, spherical nanoparticles copper oxide (CuO) and titanium oxides (TiO2) are added to SAE 15W40 engine oil to study the thermal conductivity, stability, viscosity of nano-lubricants, which are prepared at different concentrations of 0.1%, 0.2%, 0.5%, and 1% by weight, and also their pour point, and flash point as five quality parameters. The obtained results show that CuO nanoparticles in all cases, give the best functionality and effect on engine oil with respect to TiO2. With 0.1 wt. % concentration, the thermal conductivity of CuO/oil and TiO2/
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This study was conducted in the botanical garden, Department of biology, College of Science/ Mustansiriyah University in from (15 February to 15 March, 2019) under the natural environmental conditions in the greenhouse in order to evaluate the effectiveness of parsley aqueous extract as a promoter for rooting. The study included the use of aqueous extract of a plant Parsley (Petroselinum crispum) extract was used in concentrations (1.25, 2.5 g / l), compare with IBA in concentration (100 mg / L) with dipping time 24 hour for all treatments. The cutting stems were included Rosmarinus officinalis, Nerium oleander, Olea europaea, Plumeria alba, Hibiscus rosa, Pelargonium graveolens, and Myrtus communis. The following measurements were
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Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
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In this paper, we will focus to one of the recent applications of PU-algebras in the coding theory, namely the construction of codes by soft sets PU-valued functions. First, we shall introduce the notion of soft sets PU-valued functions on PU-algebra and investigate some of its related properties.Moreover, the codes generated by a soft sets PU-valued function are constructed and several examples are given. Furthermore, example with graphs of binary block code constructed from a soft sets PU-valued function is constructed.
In this paper, the penetration of the stone column was investigated in order to get the minimum length of the stone column above which the increase in length has little advantage. The effect of using different materials in column are also studied. The material used is granular of different angle of internal friction (). The results of the investigation indicated that the effect of stone column remains constant when the ratio of the thickness of the soft clay layer to the stone column’s diameter is more than 15. The results also indicated that a pronounced effect is obtained when the angle of internal friction of the stone column material is increased.
Mixed ligands of 2-benzoyl Thiobenzimiazole (L1) with 1,10-phenanthroline (L2) complexes of Cr(III) , Ni(II) and Cu(II) ions were prepared. The ligand and the complexes were isolated and characterized in solid state by using FT-IR, UV-Vis spectroscopy, 1H, 13C-NMR, flame atomic absorption, elemental micro analysis C.H.N.S, magnetic susceptibility , melting points and conductivity measurements. 2-Benzoyl thiobenzimiazole behaves as bidenetate through oxygen atom of carbonyl group and nitrogen atom of imine group. From the analyses Octahedral geometry was suggested for all prepared complexes. A theoretical treatment of ligands and their metal complexes in gas phase were studied using HyperChem-8 program, moreover, ligands in gas phase
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